What does that mean for students in our Practice Research and Evaluation courses? It means that our students are hard at work on their midterm papers describing their baselines from their own projects. To continue learning about this, we taught our students how to use several functions in SSD for R to visually and statistically analyze their data.
We showed the students how to produce and interpret one and two standard deviation band graphs in order to assess the stability of their baseline data and look for outliers. Then we taught the students how to evaluate their baselines for two problems that could impact how they compare their baseline and intervention phases, which we will begin focusing on next week. The first problem we discussed was trending while the second was autocorrelation.
Here's an example of a graph that our students were able to produce for testing for a trend by using the Aregres() function:
Autocorrelation is, perhaps, the most difficult concept we teach in this course. Most of our students have never heard of the notion of serial dependence before, and it is a fairly complicated concept to teach. The other issue with teaching students about autocorrelation is that it is not detectable visually. Our students MUST learn to interpret some statistical output!
To help our students, we have several videos posted on our website and YouTube on all of these topics.
Their mid-term papers are due next week, and we're pretty sure that our students are going to do really well with these!
Thanks so much for the videos! Very helpful.
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